DivInT

While the analysis of biodiversity has become a major topic of ecology and evolution, the diversity observed in life history trait trajectories at the individual level remains poorly understood. DivInT aims at filling this knowledge gap by (1) integrating existing data on individual trajectories of life history traits in contrasted populations of vertebrates, (2) performing standardized analyses of these trajectories within and among populations both within and across traits, (3) measuring the diversity of observed individual trajectories of phenotypic traits and fitness components, (4) identifying factors that shape the diversity of individual trajectories and quantifying their impact on population growth rate, and (5) quantifying the relative contribution of chance, constraint, and adaptation in shaping individual trajectories within and across populations. DivInT will thus provide new insight on how individual heterogeneity shapes population dynamics and life history evolution.